print.segments

result object returned by function <code><a rd-options="" href="/link/segmentClusters?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::segmentClusters">segmentClusters</a></code>

further argument to <code>print.data.frame</code>

Print method for segmentation result from <code><a rd-options="" href="/link/segmentClusters?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::segmentClusters">segmentClusters</a></code>.

A dynamic programming solution to segmentation based on
maximization of arbitrary similarity measures within segments.
The general idea, theory and this implementation are described in
Machne, Murray & Stadler (2017) <doi:10.1038/s41598-017-12401-8>.
In addition to the core algorithm, the package provides time-series
processing and clustering functions as described in the publication.
These are generally applicable where a `k-means` clustering yields
meaningful results, and have been specifically developed for
clustering of the Discrete Fourier Transform of periodic gene
expression data (`circadian' or `yeast metabolic oscillations').
This clustering approach is outlined in the supplemental material of
Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>), and here
is used as a basis of segment similarity measures. Notably, the
time-series processing and clustering functions can also be used as
stand-alone tools, independent of segmentation, e.g., for
transcriptome data already mapped to genes.

Rainer Machne

segmenTier

Similarity-Based Segmentation of Multidimensional Signals

print.segments function

result object returned by function <code><a rd-options='' href='segmentClusters'>segmentClusters</a></code>

Print method for segmentation result from <code><a rd-options='' href='segmentClusters'>segmentClusters</a></code>.

Print method for segmentation result from <code><a rd-options='' href='segmentClusters'>segmentClusters</a></code>. — print.segments

Print method for segmentation result from <code><a rd-options='' href='segmentClusters'>segmentClusters</a></code>.

Print method for segmentation result from <code><a rd-options="" href="/link/segmentClusters?package=segmenTier&version=0.1.2" data-mini-rdoc="segmenTier::segmentClusters">segmentClusters</a></code>.

print.segments: Print method for segmentation result from `segmentClusters`.

Description

Usage

Arguments